Performance model for video service in 5G networks
Yükleniyor...
Tarih
2020
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Mdpi
Erişim Hakkı
info:eu-repo/semantics/openAccess
Özet
Network slicing allows operators to sell customized slices to various tenants at different prices. To provide better-performing and cost-efficient services, network slicing is looking to intelligent resource management approaches to be aligned to users' activities per slice. In this article, we propose a radio access network (RAN) slicing design methodology for quality of service (QoS) provisioning, for differentiated services in a 5G network. A performance model is constructed for each service using machine learning (ML)-based approaches, optimized using interference coordination approaches, and used to facilitate service level agreement (SLA) mapping to the radio resource. The optimal bandwidth allocation is dynamically adjusted based on instantaneous network load conditions. We investigate the application of machine learning in solving the radio resource slicing problem and demonstrate the advantage of machine learning through extensive simulations. A case study is presented to demonstrate the effectiveness of the proposed radio resource slicing approach.
Açıklama
wang, jiao/0000-0003-3658-8662
Anahtar Kelimeler
Interference Coordination (IC), Network Slicing, 5G, Quality Of Service (QoS), Massive Multiple Input And Multiple Output (MIMO)
Kaynak
Future Internet
WoS Q Değeri
N/A
Scopus Q Değeri
Q1
Cilt
12
Sayı
6
